Paper Citation Record · LEDGER

Large Language Models are Diverse Role-Players for Summarization Evaluation

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2303.15078.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2303.15078 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:36:48.211995Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e322404a-6914-45e3-8d92-573764254254 · inbound

ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate cites this paper.

ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate Large Language Models are Diverse Role-Players for Summarization Evaluation

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-13T13:03:18.856228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b2a8bbfa-34b7-4ecc-ba1a-907dbe45672d · inbound

Instruction-Following Evaluation for Large Language Models cites this paper.

Instruction-Following Evaluation for Large Language Models Large Language Models are Diverse Role-Players for Summarization Evaluation

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-24T05:36:00.980443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 16a6dd50-1577-4b16-8e84-d866482674ec · inbound

The Prompt Report: A Systematic Survey of Prompt Engineering Techniques cites this paper.

The Prompt Report: A Systematic Survey of Prompt Engineering Techniques Large Language Models are Diverse Role-Players for Summarization Evaluation

Reference 24

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T02:16:17.916365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f2d21087-399b-46dd-9579-f986ea6fe816 · inbound

How Managers Perceive AI-Assisted Conversational Training for Workplace Communication cites this paper.

How Managers Perceive AI-Assisted Conversational Training for Workplace Communication Large Language Models are Diverse Role-Players for Summarization Evaluation

Reference 111

Resolution: unresolved; no resolver link, observed 2026-08-07T15:36:48.211995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1bc3a056-2ff9-4d9f-afb9-9f01b5a78a8b · inbound

Literature Review Of Multi-Agent Debate For Problem-Solving cites this paper.

Literature Review Of Multi-Agent Debate For Problem-Solving Large Language Models are Diverse Role-Players for Summarization Evaluation

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T12:47:37.178344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb27a574-3cee-4b88-9c87-33477ef56e88 · inbound

Evaluating Multi-Hop Reasoning in RAG Systems: A Comparison of LLM-Based Retriever Evaluation Strategies cites this paper.

Evaluating Multi-Hop Reasoning in RAG Systems: A Comparison of LLM-Based Retriever Evaluation Strategies Large Language Models are Diverse Role-Players for Summarization Evaluation

Reference 29

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T04:04:47.561856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.